Bringing Order to the Cognitive Fallacy Zoo

TL;DR

This paper introduces a formal framework to organize and relate various cognitive fallacies through implication relationships, aiming to guide future research and better understand the structure of human reasoning errors.

Contribution

It presents a novel formal approach to map relationships between cognitive fallacies using implication relationships inspired by computational complexity theory.

Findings

Examples of IRs among well-documented fallacies like base-rate neglect and framing effect.

IR framework helps identify pivotal fallacies for targeted research.

Guides systematic investigation of cognitive fallacies.

Abstract

In the eyes of a rationalist like Descartes or Spinoza, human reasoning is flawless, marching toward uncovering ultimate truth. A few centuries later, however, culminating in the work of Kahneman and Tversky, human reasoning was portrayed as anything but flawless, filled with numerous misjudgments, biases, and cognitive fallacies. With further investigations, new cognitive fallacies continually emerged, leading to a state of affairs which can fairly be characterized as the cognitive fallacy zoo! In this largely methodological work, we formally present a principled way to bring order to this zoo. We introduce the idea of establishing implication relationships (IRs) between cognitive fallacies, formally characterizing how one fallacy implies another. IR is analogous to, and partly inspired by, the fundamental concept of reduction in computational complexity theory. We present several examples of IRs involving experimentally well-documented cognitive fallacies: base-rate neglect, availability bias, conjunction fallacy, decoy effect, framing effect, and Allais paradox. We conclude by discussing how our work: (i) allows for identifying those pivotal cognitive fallacies whose investigation would be the most rewarding research agenda, and importantly (ii) permits a systematized, guided research program on cognitive fallacies, motivating influential theoretical as well as experimental avenues of future research.